Flood Inundation Mapping and Spatial Analysis: A Case Study of the 2022 Massive Flood in Swat, Khyber Pakhtunkhwa, Pakistan

Atta Ullah; Saddique Akbar; Muhammad Afan Ghani; Muhammad Paryal; Muhammad Maaz; Noman Ali Shah; Imtiaz Momand

doi:10.52562/injoes.2025.1398

Authors

Atta Ullah State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100080, China | University of Chinese Academy of Sciences, Beijing 100049, China
Saddique Akbar State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100080, China | University of Chinese Academy of Sciences, Beijing 100049, China
Muhammad Afan Ghani University of Engineering and Technology, Peshawar 54890, Pakistan
Muhammad Paryal State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100080, China | University of Chinese Academy of Sciences, Beijing 100049, China
Muhammad Maaz Department of Environmental Sciences, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad 45320, Pakistan
Noman Ali Shah State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, School of Environment, Northeast Normal University, Changchun 130117, China
Imtiaz Momand Pakhtunkhwa Energy Development Organization (PEDO) KPK, Peshawar, Pakistan

DOI:

https://doi.org/10.52562/injoes.2025.1398

Keywords:

Flood, Swat, Climate change, Inundation

Abstract

Climate change has increased the frequency of extreme precipitation, increasing rapid flood risks globally. This study integrates remote sensing, geospatial data and climatic statistics to map flood inundation and analyze precipitation patterns in Swat district, Khyber Pakhtunkhwa, Pakistan, following the 2022 flood. We used Google Earth Engine (GEE), applied supervised classification on sentinel-2 imagery achieving an accuracy of 99.7% for 2021 and 97.3% for 2022, confirming the precision of our analysis. Flood water body levels were meticulously scrutinized, culminating in the production of an illuminating flood inundation map through the Summer Permanent Water Bodies (SPWB) exclusion layer and Normalized Difference Flood Index (NDFI) framework. The NDVI and SPWB exclusion layer identified 1230 km² of inundated area and 258 km² of land use change in 2022. Analysis of Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) summer precipitation data revealed a peak of 877 mm in 2022, with significant increase in southern, central and northern parts of Swat. This study is an earnest attempt to advance our understanding of flood mapping and offer roadmap for enhanced disaster management, supporting urban planning and mitigation strategies in the flood prone regions of Swat.

Downloads

Download data is not yet available.

References

Abbas, A., Bhatti, A. S., Ullah, S., Ullah, W., Waseem, M., Zhao, C., Dou, X., & Ali, G. (2023). Projection of precipitation extremes over South Asia from CMIP6 GCMs. Journal of Arid Land, 15(3), 274-296. https://doi.org/10.1007/s40333-023-0050-3

Abbas, A., Ullah, S., Ullah, W., Waseem, M., Dou, X., Zhao, C., Karim, A., Zhu, J., Hagan, D. F. T., Bhatti, A. S., & Ali, G. (2022). Evaluation and projection of precipitation in Pakistan using the Coupled Model Intercomparison Project Phase 6 model simulations. International Journal of Climatology, 42(13), 6665-6684. https://doi.org/https://doi.org/10.1002/joc.7602

Ahmed, E., Saddique, N., Al Janabi, F., Barfus, K., Asghar, M. R., Sarwar, A., & Krebs, P. (2023). Flood Predictability of One-Way and Two-Way WRF Nesting Coupled Hydrometeorological Flow Simulations in a Transboundary Chenab River Basin, Pakistan. Remote Sensing, 15(2), 457. https://www.mdpi.com/2072-4292/15/2/457

Akbar, S., Junbo, W., Atta, U., Yasir, L., & and Muhammad, S. (2024). The growth and emergence of potentially dangerous glacier lakes in Astore Basin, Western Himalaya during 1993–2021. Geomatics, Natural Hazards and Risk, 15(1), 2353838. https://doi.org/10.1080/19475705.2024.2353838

Alam, A., Bhat, M. S., Kotlia, B. S., Ahmad, B., Ahmad, S., Taloor, A. K., & Ahmad, H. F. (2018). Hybrid tectonic character of the Kashmir basin: response to comment on “Coexistent pre-existing extensional and subsequent compressional tectonic deformation in the Kashmir basin, NW Himalaya (Alam et al., 2017)” by Shah (2017). Quaternary International, 468, 284-289.

Almazroui, M., Saeed, S., Saeed, F., Islam, M. N., & Ismail, M. (2020). Projections of Precipitation and Temperature over the South Asian Countries in CMIP6. Earth Systems and Environment, 4(2), 297-320. https://doi.org/10.1007/s41748-020-00157-7

Atta ur, R., & Khan, A. N. (2013). Analysis of 2010-flood causes, nature and magnitude in the Khyber Pakhtunkhwa, Pakistan. Natural Hazards, 66(2), 887-904. https://doi.org/10.1007/s11069-012-0528-3

Baqa, M. F., Lu, L., Chen, F., Nawaz-ul-Huda, S., Pan, L., Tariq, A., Qureshi, S., Li, B., & Li, Q. (2022). Characterizing Spatiotemporal Variations in the Urban Thermal Environment Related to Land Cover Changes in Karachi, Pakistan, from 2000 to 2020. Remote Sensing, 14(9), 2164. https://www.mdpi.com/2072-4292/14/9/2164

Baqir, M., Sobani, Z. A., Bhamani, A., Bham, N. S., Abid, S., Farook, J., & Beg, M. A. (2012). Infectious diseases in the aftermath of monsoon flooding in Pakistan. Asian Pacific Journal of Tropical Biomedicine, 2(1), 76-79. https://doi.org/https://doi.org/10.1016/S2221-1691(11)60194-9

Bhatti, A. S., Wang, G., Ullah, W., Ullah, S., Fiifi Tawia Hagan, D., Kwesi Nooni, I., Lou, D., & Ullah, I. (2020). Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan. Water, 12(3), 797. https://www.mdpi.com/2073-4441/12/3/797

Billa, L., Shattri, M., Rodzi Mahmud, A., & Halim Ghazali, A. (2006). Comprehensive planning and the role of SDSS in flood disaster management in Malaysia. Disaster Prevention and Management: An International Journal, 15(2), 233-240. https://doi.org/10.1108/09653560610659775

Butt, A., Aslam, H. M. U., Shabir, H., Javed, M., Hussain, S., Nadeem, S., Raza, H., Haroon, S., & Arshad, S. (2020). Climatic Events and Natural Disasters of 21st Century: A Perspective of Pakistan.

Chen, Y., Opa?a-Owczarek, M., Chen, F., Owczarek, P., Zhang, H., Wang, S., Hu, M., Satylkanov, R., Ermenbaev, B., Zulfiyor, B., Shang, H., & Zhang, R. (2023). Tree-ring perspective on past and future mass balance of the glaciers in Tien Shan (Central Asia): An example from the accumulation area of Tuyuksu Glacier, Kazakhstan. Palaeogeography, Palaeoclimatology, Palaeoecology, 625, 111696. https://doi.org/https://doi.org/10.1016/j.palaeo.2023.111696

Cheng, J., & Liang, S. (2018). 5.10 - Land-Surface Emissivity. In S. Liang (Ed.), Comprehensive Remote Sensing (pp. 217-263). Elsevier. https://doi.org/https://doi.org/10.1016/B978-0-12-409548-9.10374-4

Cian, F., Marconcini, M., & Ceccato, P. (2018). Normalized Difference Flood Index for rapid flood mapping: Taking advantage of EO big data. Remote sensing of environment, 209, 712-730. https://doi.org/https://doi.org/10.1016/j.rse.2018.03.006

de Kok, J.-L., & Grossmann, M. (2010). Large-scale assessment of flood risk and the effects of mitigation measures along the Elbe River. Natural Hazards, 52(1), 143-166. https://doi.org/10.1007/s11069-009-9363-6

Dereli, T., Eligüzel, N., & Çetinkaya, C. (2021). Content analyses of the international federation of red cross and red crescent societies (ifrc) based on machine learning techniques through twitter. Natural Hazards, 106, 2025-2045.

Díez-Herrero, A., & Garrote, J. (2020). Flood risk analysis and assessment, applications and uncertainties: A bibliometric review. Water, 12(7), 2050.

Ernst, J., Dewals, B. J., Detrembleur, S., Archambeau, P., Erpicum, S., & Pirotton, M. (2010). Micro-scale flood risk analysis based on detailed 2D hydraulic modelling and high resolution geographic data. Natural Hazards, 55(2), 181-209. https://doi.org/10.1007/s11069-010-9520-y

Farooq, M., Shafique, M., & Khattak, M. S. (2019). Flood hazard assessment and mapping of River Swat using HEC-RAS 2D model and high-resolution 12-m TanDEM-X DEM (WorldDEM). Natural Hazards, 97(2), 477-492. https://doi.org/10.1007/s11069-019-03638-9

Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., & Michaelsen, J. (2015). The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Scientific Data, 2(1), 150066. https://doi.org/10.1038/sdata.2015.66

Gao, B.-c. (1996). NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space. Remote sensing of environment, 58(3), 257-266. https://doi.org/https://doi.org/10.1016/S0034-4257(96)00067-3

Gaurav, K., Sinha, R., & Panda, P. K. (2011). The Indus flood of 2010 in Pakistan: a perspective analysis using remote sensing data. Natural Hazards, 59(3), 1815-1826. https://doi.org/10.1007/s11069-011-9869-6

Hajjar, R., Oldekop, J. A., Cronkleton, P., Newton, P., Russell, A. J., & Zhou, W. (2021). A global analysis of the social and environmental outcomes of community forests. Nature sustainability, 4(3), 216-224. https://doi.org/10.1038/s41893-020-00633-y

Huang, Y., Shi, W., Fu, Q., Qiu, Y., Zhao, J., Li, J., Lyu, Q., Yang, X., Xiong, J., Wang, W., Chang, R., Yao, Z., Dai, Z., Qiu, Y., & Chen, H. (2023). Soil development following glacier retreat shapes metagenomic and metabolomic functioning associated with asynchronous C and N accumulation. Science of the Total Environment, 892, 164405. https://doi.org/https://doi.org/10.1016/j.scitotenv.2023.164405

Jones, K., Lanthier, Y., van der Voet, P., van Valkengoed, E., Taylor, D., & Fernández-Prieto, D. (2009). Monitoring and assessment of wetlands using Earth Observation: The GlobWetland project. Journal of Environmental Management, 90(7), 2154-2169. https://doi.org/https://doi.org/10.1016/j.jenvman.2007.07.037

Kannaujiya, S., Gautam, P. K., Chauhan, P., Roy, P. N. S., Pal, S. K., & Taloor, A. K. (2021). Contribution of seasonal hydrological loading in the variation of seismicity and geodetic deformation in Garhwal region of Northwest Himalaya. Quaternary International, 575, 62-71.

Kawo, N. S., Hordofa, A. T., & Karuppannan, S. (2021). Performance evaluation of GPM-IMERG early and late rainfall estimates over Lake Hawassa catchment, Rift Valley Basin, Ethiopia. Arabian Journal of Geosciences, 14(4), 256.

Khan, N. A., Alzahrani, H., Bai, S., Hussain, M., Tayyab, M., Ullah, S., Ullah, K., & Khalid, S. (2025). Flood risk assessment in the Swat river catchment through GIS-based multi-criteria decision analysis. Frontiers in Environmental Science, 13, 1567796. https://doi.org/10.3389/fenvs.2025.1567796

Khan, A. A., Jamil, A., Hussain, D., Taj, M., Jabeen, G., & Malik, M. K. (2020). Machine-learning algorithms for mapping debris-covered glaciers: The Hunza Basin case study. Ieee Access, 8, 12725-12734.

Khan, I., Ali, A., Waqas, T., Ullah, S., Ullah, S., Shah, A. A., & Imran, S. (2022). Investing in disaster relief and recovery: A reactive approach of disaster management in Pakistan. International Journal of Disaster Risk Reduction, 75, 102975. https://doi.org/https://doi.org/10.1016/j.ijdrr.2022.102975

Khan, I., Lei, H., Shah, A. A., Khan, I., & Muhammad, I. (2021). Climate change impact assessment, flood management, and mitigation strategies in Pakistan for sustainable future. Environmental Science and Pollution Research, 28(23), 29720-29731. https://doi.org/10.1007/s11356-021-12801-4

Lehmann, J., Coumou, D., & Frieler, K. (2015). Increased record-breaking precipitation events under global warming. Climatic change, 132. https://doi.org/10.1007/s10584-015-1466-3

Liu, J., Liu, K., & Wang, M. (2023). A Residual Neural Network Integrated with a Hydrological Model for Global Flood Susceptibility Mapping Based on Remote Sensing Datasets. Remote Sensing, 15(9), 2447. https://www.mdpi.com/2072-4292/15/9/2447

Mahmood, R., & Jia, S. (2019). Assessment of hydro-climatic trends and causes of dramatically declining stream flow to Lake Chad, Africa, using a hydrological approach. Science of the Total Environment, 675, 122-140.

Mahto, S. S., & Mishra, V. (2019). Does ERA-5 Outperform Other Reanalysis Products for Hydrologic Applications in India? Journal of Geophysical Research: Atmospheres, 124(16), 9423-9441. https://doi.org/https://doi.org/10.1029/2019JD031155

Majeed, M., Lu, L., Anwar, M. M., Tariq, A., Qin, S., El-Hefnawy, M. E., El-Sharnouby, M., Li, Q., & Alasmari, A. (2023). Prediction of flash flood susceptibility using integrating analytic hierarchy process (AHP) and frequency ratio (FR) algorithms [Original Research]. Frontiers in Environmental Science, 10. https://doi.org/10.3389/fenvs.2022.1037547

Malik, M. I., & Ahmad, F. (2014). Flood Inundation Mapping and Risk Zoning of the Swat River Pakistan using HEC-RAS Model.

Mirza, M. M. Q. (2011). Climate change, flooding in South Asia and implications. Regional Environmental Change, 11(1), 95-107. https://doi.org/10.1007/s10113-010-0184-7

Monserud, R. A., & Leemans, R. (1992). Comparing global vegetation maps with the Kappa statistic. Ecological Modelling, 62(4), 275-293. https://doi.org/https://doi.org/10.1016/0304-3800(92)90003-W

Nanditha, J. S., Kushwaha, A. P., Singh, R., Malik, I., Solanki, H., Chuphal, D. S., Dangar, S., Mahto, S. S., Vegad, U., & Mishra, V. (2023). The Pakistan Flood of August 2022: Causes and Implications. Earth's Future, 11(3), e2022EF003230. https://doi.org/https://doi.org/10.1029/2022EF003230

Nasir, M. J., Iqbal, J., & Ahmad, W. (2020). Flash flood risk modeling of swat river sub-watershed: a comparative analysis of morphometric ranking approach and El-Shamy approach. Arabian Journal of Geosciences, 13(20), 1082. https://doi.org/10.1007/s12517-020-06064-5

NDMA. (2022). National disaster management authority, Pakistan.

Otto, F., Zachariah, M., Saeed, F., Siddiqi, A., Shahzad, K., Mushtaq, H., Achutarao, K., S T, C., Barnes, C., Philip, S., Thalheimer, L., Raju, E., Li, S., Yang, W., Harrington, L., & Clarke, B. (2022). Final Climate change likely increased extreme monsoon rainfall, flooding highly vulnerable communities in Pakistan.

Owusu, M., Nursey-Bray, M., & Rudd, D. (2019). Gendered perception and vulnerability to climate change in urban slum communities in Accra, Ghana. Regional Environmental Change, 19. https://doi.org/10.1007/s10113-018-1357-z

Paulikas, M. J., & Rahman, M. K. (2015). A temporal assessment of flooding fatalities in Pakistan (1950–2012). Journal of Flood Risk Management, 8(1), 62-70. https://doi.org/https://doi.org/10.1111/jfr3.12084

PMD. (2022). Pakistan Meteorological Department.

Rahman, Z. U., Ullah, W., Bai, S., Ullah, S., Jan, M. A., Khan, M., & Tayyab, M. (2023). GIS-based flood susceptibility mapping using bivariate statistical model in Swat River Basin, Eastern Hindukush region, Pakistan. Frontiers in Environmental Science, 11, 1178540. https://doi.org/10.3389/fenvs.2023.1178540

Rebi, A., Hussain, A., Hussain, I., Cao, J., Ullah, W., Abbas, H., Ullah, S., & Zhou, J. (2023). Spatiotemporal Precipitation Trends and Associated Large-Scale Teleconnections in Northern Pakistan. Atmosphere, 15, 871. https://doi.org/10.3390/atmos14050871

Rentschler, J., Salhab, M., & Jafino, B. A. (2022). Flood exposure and poverty in 188 countries. Nat Commun, 13(1), 3527. https://doi.org/10.1038/s41467-022-30727-4

Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1973). Monitoring vegetation systems in the great plains with ERTS.

Saeed, M., Li, H., Ullah, S., Rahman, A.-u., Ali, A., Khan, R., Hassan, W., Munir, I., & Alam, S. (2021). Flood Hazard Zonation Using an Artificial Neural Network Model: A Case Study of Kabul River Basin, Pakistan. Sustainability, 13(24), 13953. https://www.mdpi.com/2071-1050/13/24/13953

Sakurai, M., & Murayama, Y. (2019). Information technologies and disaster management–Benefits and issues. Progress in Disaster Science, 2, 100012.

Samanta, S., Pal, D. K., & Palsamanta, B. (2018). Flood susceptibility analysis through remote sensing, GIS and frequency ratio model. Applied Water Science, 8(2), 66. https://doi.org/10.1007/s13201-018-0710-1

Sarhadi, A., Soltani, S., & Modarres, R. (2012). Probabilistic flood inundation mapping of ungauged rivers: Linking GIS techniques and frequency analysis. Journal of Hydrology, 458-459, 68-86. https://doi.org/https://doi.org/10.1016/j.jhydrol.2012.06.039

Sarkar, D., & Mondal, P. (2019). Flood vulnerability mapping using frequency ratio (FR) model: a case study on Kulik river basin, Indo-Bangladesh Barind region. Applied Water Science, 10(1), 17. https://doi.org/10.1007/s13201-019-1102-x

Shah, A. A., Ullah, A., Khan, N. A., Shah, M. H., Ahmed, R., Hassan, S. T., Tariq, M. A. U. R., & Xu, C. (2023). Identifying obstacles encountered at different stages of the disaster management cycle (DMC) and its implications for rural flooding in Pakistan [Original Research]. Frontiers in Environmental Science, 11. https://doi.org/10.3389/fenvs.2023.1088126

Shen, L., Wen, J., Zhang, Y., Ullah, S., Cheng, J., & Meng, X. (2022). Changes in population exposure to extreme precipitation in the Yangtze River Delta, China. Climate Services, 27, 100317. https://doi.org/https://doi.org/10.1016/j.cliser.2022.100317

Taloor, A. K., Kumar, V., Singh, V. K., Singh, A. K., Kale, R. V., Sharma, R., Khajuria, V., Raina, G., Kouser, B., & Chowdhary, N. H. (2020). Land use land cover dynamics using remote sensing and GIS Techniques in Western Doon Valley, Uttarakhand, India. Geoecology of landscape dynamics, 37-51.

Tariq, A., Mumtaz, F., Majeed, M., & Zeng, X. (2022). Spatio-temporal assessment of land use land cover based on trajectories and cellular automata Markov modelling and its impact on land surface temperature of Lahore district Pakistan. Environmental Monitoring and Assessment, 195(1), 114. https://doi.org/10.1007/s10661-022-10738-w

Tsering, K., Shrestha, M., Shakya, K., Bajracharya, B., Matin, M., Lozano, J. L. S., Nelson, J., Wangchuk, T., Parajuli, B., & Bhuyan, M. A. (2022). Verification of two hydrological models for real-time flood forecasting in the Hindu Kush Himalaya (HKH) region. Natural Hazards, 110(3), 1821-1845. https://doi.org/10.1007/s11069-021-05014-y

Uddin, K., Gurung, D. R., Giriraj, A., & Shrestha, B. (2013). Application of Remote Sensing and GIS for Flood Hazard Management: A Case Study from Sindh Province, Pakistan. American Journal of Geographic Information System, 2013, 1-5. https://doi.org/10.5923/j.ajgis.20130201.01

Uddin, K., Matin, M. A., & Thapa, R. B. (2021). Rapid Flood Mapping Using Multi-temporal SAR Images: An Example from Bangladesh. A Decade of Experience from SERVIR, 201.

Ullah, F., Ali Shah, S. A., Saqib, S. E., Yaseen, M., & Haider, M. S. (2021). Households’ flood vulnerability and adaptation: Empirical evidence from mountainous regions of Pakistan. International Journal of Disaster Risk Reduction, 52, 101967. https://doi.org/https://doi.org/10.1016/j.ijdrr.2020.101967

Ullah, S., Liu, S., Adnan, M., Ashraf, M., Zaman, D. M., Hashim, S., & Muhammad, S. (2020). Risks of Glaciers Lakes Outburst Flood along China Pakistan Economic Corridor. In (pp. 1-17). https://doi.org/10.5772/intechopen.93459

UNDRR. (2020). Human cost of disasters: An Overview of the Last 20 Years (2000-2019). The Centre for Research on the Epidemiology of Disasters (CRED.

USGS. (2019). United States Geological Society. https://www.usgs.gov/landsat-missions/landsat-normalized-difference-vegetation-index

Verpoorter, C., Kutser, T., & Tranvik, L. (2012). Automated mapping of water bodies using Landsat multispectral data. Limnology and Oceanography: Methods, 10(12), 1037-1050. https://doi.org/https://doi.org/10.4319/lom.2012.10.1037

Wattanachareekul, P., Choowong, N., Pailoplee, S., & Choowong, M. (2023). Resilience to unusual flooding after 2021 tropical storms in part of mainland Southeast Asia. Frontiers in Ecology and Evolution, 10, 1072993. https://doi.org/10.3389/fevo.2022.1072993

Xu, C., Zhang, X., Zhang, J., Chen, Y., Yami, T., & Hong, Y. (2021). Estimation of Crop Water Requirement Based on Planting Structure Extraction from Multi-Temporal MODIS EVI. Water Resources Management, 35, 1-17. https://doi.org/10.1007/s11269-021-02838-y

Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, 27, 3025 - 3033.

Xue, F., Gao, W., Yin, C., Chen, X., Xia, Z., Lv, Y., Zhou, Y., & Wang, M. (2022). Flood Monitoring by Integrating Normalized Difference Flood Index and Probability Distribution of Water Bodies. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 4170-4179. https://doi.org/10.1109/JSTARS.2022.3176388

Yaqub, M., & Eren, B. (2015). Flood Causes, Consequences and Protection Measures in Pakistan[#381757]-408170. 1, 8-16.

Yi, C.-S., Lee, J.-H., & Shim, M.-P. (2010). GIS-based distributed technique for assessing economic loss from flood damage: pre-feasibility study for the Anyang Stream Basin in Korea. Natural Hazards, 55(2), 251-272. https://doi.org/10.1007/s11069-010-9524-7

Zhang, W., Furtado, K., Wu, P., Zhou, T., Chadwick, R., Marzin, C., Rostron, J., & Sexton, D. (2021). Increasing precipitation variability on daily-to-multiyear time scales in a warmer world. Science Advances, 7(31), eabf8021.

Zhou, L., Zhou, Y., de Vries, W. T., Liu, Z., & Sun, H. (2024). Collective action dilemmas of sustainable natural resource management: A case study on land marketization in rural China. Journal of Cleaner Production, 439, 140872. https://doi.org/10.1016/j.jclepro.2024.140872

Zou, Q., Zhou, J., Zhou, C., Song, L., & Guo, J. (2013). Comprehensive flood risk assessment based on set pair analysis-variable fuzzy sets model and fuzzy AHP. Stochastic Environmental Research and Risk Assessment, 27(2), 525-546. https://doi.org/10.1007/s00477-012-0598-5